Comparison of the impact of <i>trans</i> fatty acids from ruminants and industrial sources on human cholesterol homeostasis
Bibliographic record
Abstract
This double‐blind randomized crossover study compared the impact of dietary trans fatty acids (TFA) from ruminants (rTFA) and from industrial sources (iTFA) on surrogate markers of cholesterol absorption (β‐sitosterol and campesterol) and synthesis (lathosterol) in healthy men. Thirty‐eight men consumed 3 experimental isoenergetic diets in a random order for 4 weeks each. The 3 diets were 1) high in rTFA (10.2g/2500 kcal), 2) high in iTFA (10.2g/2500 kcal) and 3) control diet low in TFA from any source (2.2g/2500 kcal). Plasma LDL‐C concentrations were increased to a similar extent in the iTFA (+4%) and rTFA (+6%) diets compared with the control diet. Plasma concentrations of β‐sitosterol, campesterol and lathosterol were significantly reduced after the iTFA diet compared with the control diet (−11%, −26% and −17% respectively, P < 0.05), but not after the rTFA diet. Analyses were also performed according to baseline concentrations of absorption markers. Low absorbers on the control diet had a 29% increase in plasma LDL‐C concentrations after the rTFA diet (P = 0.01 vs. the control diet) but showed no significant change in LDL‐C after the iTFA diet (+11%, P = 0.23). While very high intakes of rTFA and iTFA appear to have comparable LDL‐C raising effects, our data suggest that underlying mechanisms may be different between the two sources of TFA. Financial support: Dairy Farmers of Canada, Novalait Inc and NSERC
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".